--- size_categories: n<1K tags: - rlfh - argilla - human-feedback --- # Dataset Card for Q1652 This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets). ## Using this dataset with Argilla To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code: ```python import argilla as rg ds = rg.Dataset.from_hub("ClimatePolicyRadar/Q1652", settings="auto") ``` This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation. ## Using this dataset with `datasets` To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code: ```python from datasets import load_dataset ds = load_dataset("ClimatePolicyRadar/Q1652") ``` This will only load the records of the dataset, but not the Argilla settings. ## Dataset Structure This dataset repo contains: * Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`. * The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla. * A dataset configuration folder conforming to the Argilla dataset format in `.argilla`. The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**. ### Fields The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset. | Field Name | Title | Type | Required | Markdown | | ---------- | ----- | ---- | -------- | -------- | | text | Text | text | True | True | ### Questions The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking. | Question Name | Title | Type | Required | Description | Values/Labels | | ------------- | ----- | ---- | -------- | ----------- | ------------- | | entities | entities | span | True | N/A | N/A | ### Data Instances An example of a dataset instance in Argilla looks as follows: ```json { "_server_id": "4026704f-0659-4939-b886-904d6e239dd1", "fields": { "text": "26 Central Statistical Agency. \"Ethiopia 2013 Labour Force Survey Addis Ababa. Last modified 2014. https://www.ilo.org/surveyLib/index.php/ catalog/7142/download/43668\n-----\nThe objective of this chapter is threefold. First, it presents estimates of investments needed to achieve NZE by mid-century under the three selected scenarios. Second, it estimates the gap between the needed and available investments to meet the net-zero targets. Third, it reviews the strategy to close the financial gap by describing the financing options associated with costs estimates derived from the CBA. The technical annex shows the assumptions, modelling definitions, and interventions that guided the financing actions of the LT-LEDS.\n-----\nThis chapter provides a data-driven blueprint, aligned with and complementary to the existing national climate finance policies and strategies for financing the transition to a zero-emission and climate-resilient pathway by mid-century." }, "id": "997ca298-0bad-41d5-a9b4-6b68343bf39e", "metadata": { "coords": [ [ 322, 479 ], [ 539, 479 ], [ 539, 616 ], [ 322, 616 ] ], "document_content_type": "application/pdf", "document_id": "UNFCCC.party.1745.0", "document_metadata.author": [ "Ethiopia" ], "document_metadata.author_is_party": true, "document_metadata.collection_id": "nan", "document_metadata.date": "2023-06-21", "document_metadata.family_id": "nan", "document_metadata.family_name": "Ethiopia\u0027s long term low emission and climate resilient development strategy (2020-2050)", "document_metadata.family_slug": "nan", "document_metadata.geography_iso": "ETH", "document_metadata.role": "MAIN", "document_metadata.source": "GST", "document_metadata.status": "nan", "document_metadata.types": [ "Long-Term Low-Emission Development Strategy" ], "document_metadata.variant": "nan", "document_name": "Ethiopia\u0027s long term low emission and climate resilient development strategy (2020-2050)", "document_source_url": "t/sites/default/files/resource/ETHIOPIA_%20LONG%20TERM%20LOW%20EMISSION%20AND%20CLIMATE%20RESILIENT%20DEVELOPMENT%20STRATEGY.pdf", "has_valid_text": true, "language": "en", "languages": [ "en" ], "page_number": 91, "text": [ "echnical annex shows the assumptions, modelling definitions, and interventions that guided the financing actions of the LT-LEDS." ], "text_block_id": "p_91_b_0", "translated": false, "type": "Text", "type_confidence": 0.9975045323371887 }, "responses": { "entities": [ { "user_id": "19cc536b-c98d-4033-9880-b40477b55515", "value": [ { "end": 963, "label": "Q1652", "score": null, "start": 904 } ] } ] }, "status": "completed", "suggestions": {}, "vectors": {} } ``` While the same record in HuggingFace `datasets` looks as follows: ```json null ``` ### Data Splits The dataset contains a single split, which is `train`. ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation guidelines Highlight the entity if it is present in the text #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions [More Information Needed]